Long Term Evolution (LTE) is the fourth-generation mobile communication technologies standard developed within the 3rd Generation Partnership Project (3GPP) to improve the Universal Mobile Telecommunication System (UMTS) standard to cope with future requirements in terms of improved services such as higher data rates, improved efficiency, and lowered costs. The Universal Terrestrial Radio Access Network (UTRAN) is the radio access network of a UMTS and Evolved UTRAN (E-UTRAN) is the radio access network of an LTE system. In an E-UTRAN, a User Equipment (UE) is wirelessly connected to a Radio Base Station (RBS) commonly referred to as an evolved NodeB (eNodeB). An RBS is a general term for a radio network node capable of transmitting radio signals to a UE and receiving signals transmitted by a UE.
FIG. 1 illustrates a conventional radio access network in an LTE system. An eNodeB 100 with a transmission point 101 serves a UE 103 located within the eNodeB's geographical area of service also called a cell 105. The eNodeB 100 manages the radio resources in its cell 105 and is directly connected to the CN (not illustrated). The eNodeB 100 is also connected via an X2 interface to a neighboring eNodeB 150 with a transmission point 151 serving another cell 155.
Radio Resource Management (RRM) plays a crucial role in how resources in a wireless communications system are used. In particular, RRM techniques in wireless communications systems are of high importance as they largely influence how efficiently the system is used. Two RRM functionalities, scheduling and Link Adaptation (LA), play a central role for resource allocation and have a significant influence on system performance. These two RRM functionalities work tightly together. The scheduling allocates a certain part of a spectrum, i.e. of the available frequency resources, to a certain UE during a certain amount of time. The LA computes how many bits that may be transmitted in the scheduled part of the frequency resource given operating channel conditions, a transmit power and a desired probability of a correct reception. LA is thus a matching of the modulation, coding and other signal and protocol parameters to the conditions on the radio link such as the pathloss, and the interference due to signals coming from other transmitters.
The scheduling and LA are used in a way that optimizes a frequency resource utilization in every cell separately. Other RRM functionalities promote the coordination between different cells, and are also very important for a good wireless communications system performance. There are for instance schemes that try to mitigate and coordinate interference among different cells, commonly referred to as Inter-Cell Interference Coordination (ICIC) schemes. ICIC schemes try to coordinate a generated inter-cell interference between cells so that the effect of the generated interference becomes less detrimental, typically by utilizing feedback and exchanging information between neighboring radio base stations. ICIC schemes usually work on a slower basis than the scheduling and LA in order to mitigate the increased overhead and complexity arising from the extra information exchange, signaling, and processing needed for ICIC.
A main operating principle in conventional scheduling and LA is to transmit as many data bits as possible given a certain frequency resource allocation, or expressed in another way, to find a smallest possible frequency resource allocation given a certain number of data bits to transmit. At the same time, a certain probability of correct reception under the operating channel conditions should be satisfied. A commonly used criterion for the probability of correct reception is a Block Error Rate (BLER) target.
LA requires channel state information at the transmitter. This could be acquired in time division duplex systems by assuming that the channel from the transmitter to the receiver is approximately the same as the channel from the receiver to the transmitter. Alternatively, the channel knowledge can also be directly measured at the receiver, and fed back to the transmitter. LA improves the rate of transmission, and/or the bit error rates, by exploiting the channel state information that is present at the transmitter.
Channel Quality Indicator (CQI) is an indicator of the communication quality of wireless channels. CQI can be a value or values indicating a measure of channel quality for a given channel. Typically, a high value of CQI is indicative of a channel with high quality and vice versa. A CQI for a channel can be computed by making use of performance metrics, such as a Signal-to-Noise Ratio (SNR), Signal-to-Interference plus Noise Ratio (SINR), and Signal-to-Noise plus Distortion Ratio (SNDR) for the channel. These values and others can be measured for a given channel and may then be used to determine a CQI for the channel.
LA based on CQI measurements made by the UE and reported to the RBS has been employed in wireless networks for a long time. However, due to the delay between feedback timing and scheduling timing, the RBS has to use an “old” measurement result to estimate the CQI, predict the channel quality, and decide the LA parameters, such as the Modulation and Coding Scheme (MCS) for the next scheduled occasion for a UE transmission.
Furthermore, since channel quality prediction errors always exist, e.g. due to rapid channel variations and CQI estimation errors, the LA accuracy may be impaired. This may eventually lead to a lower throughput. Hereinafter, two conventional methods to improve LA quality are described.
1) Open-Loop LA (OLLA):
OLLA is an improved LA mechanism on the network side. The acknowledgement/non-acknowledgement (ACK/NACK) feedback from a hybrid automatic repeat request (HARQ) procedure is used to assist in the MCS decision. When a packet transmitted with a given MCS is successfully received by the UE, that is when the RBS receives an ACK associated with the packet, the channel quality prediction is increased by a small step. On the other hand, if the RBS receives a NACK associated with the packet, which means that the packet is not successfully received by the UE, the channel quality prediction is decreased by a large step. By tuning the step sizes, the BLER can be kept at a given level, e.g. 10%, and the throughput can be optimized. The channel quality prediction tuning is accumulative. The OLLA mechanism can be formulized according to the following:SINROLLA=CQIorg−Step_acc  (1)where SINROLLA denotes the OLLA-adjusted channel quality indicator. An accumulative step, Step_acc, is thus deduced from the original CQI, CQIorg, to obtain the SINROLLA. CQIorg may be filtered.
2) Coordinated Scheduling:
Coordinated scheduling in the scope of ICIC, enables another way to mitigate the impact from inter-cell interference. The eNodeBs may share scheduling info, including transmission power levels, in order to adjust the CQI based on it for use in LA.
However, the accuracy of LA in cellular networks can be seriously impaired by unexpected inter-cell interference variation as well as own signal variation, even if OLLA and coordinated scheduling is employed, as will be described hereinafter.
To keep a certain quality of service, OLLA has to be conservative for a wireless system. In a typical configuration of OLLA, the increasing step is configured to be 1/10 of the decreasing step. In this way a 10% BLER can be achieved to balance the downlink throughput and the transmission delay. A sharp SINR decrease in the time domain may therefore be captured, such that a lower channel quality prediction is used to secure successful transmission. However, a sharp SINR increase in time domain cannot be captured as fast as the SINR decrease due to the size difference between the increasing and the decreasing step.
A SINR variation caused by an unexpected inter-cell interference variation could be due to three reasons: a variation of the interfering cell signal due to a variation of transmission power in the interfering cell, a variation of the interfering cell signal due to slow fading, or a variation of the interfering cell signal due to fast fading. The SINR variation caused by the own cell signal variation could be due to slow fading or fast fading.
Fast fading variations may be mitigated by time-domain filtering. SINR variations due to a variation of transmission power in the interfering cell can be predicted by using information received from interfering neighbors via coordinated scheduling. However, a rapid variation of a slow fading, which may be the case when the UE is moving fast, is not possible to predict with current LA methods.
FIG. 2 illustrates an example scenario of when a rapid variation of slow fading is present for a UE 203, due to that the UE 203 is used by a user in a vehicle rapidly passing by a building 202 hindering the signal path from a transmission point 201, and thus creating rapid variations of the slow fading when passing from area A to area B, as well as from area B to area C. Area B is the area shadowed by the building 202. If it is assumed that the transmission point 201 corresponds to an eNodeB hosting the serving cell of the UE, the radio channel quality, e.g. measured as the SINR, drops sharply when the car moves from area A to area B. As the UE moves rapidly, there is a high probability that the SINR drop happens before the next CQI report update arrives. If the OLLA mechanism in accordance with formula [1] above is used, the channel quality prediction estimation SINROLLA will be reduced by large accumulative steps, Step_acc, in order to adapt the SINROLLA to the true channel quality. However, the Step_acc will not be reset at once when SINR increases again, since the eNodeB does not know whether Step_acc is used to compensate for a channel quality variation or a channel estimation error. When the original CQI, CQIorg, is updated later based on a new CQI report, the UE may already be in area C, and the reduced Step_acc has resulted in a scheduled throughput that is lower than it should have been.
If it is assumed that the transmission point 201 in FIG. 2 corresponds to an eNodeB hosting a cell which is the cell interfering the UE 203, the interference is decreased when the UE moves from area A to area B. The UE will use Step_acc to mitigate the interference variation. However, the channel quality prediction is increased by a small step for each received ACK. The OLLA mechanism requires a lot of ACK from the UE to be sure that the air interface and the channel really has become better. Therefore, the modification of SINROLLA may take quite some time.
Even if the pathloss value for the UE associated with the interfering cell does not vary as is does in FIG. 2 when the transmission point 201 transmits the interfering cell, there may still be a variation of the interference due to that the downlink transmission from the interfering cell varies in the time domain. The interference may thus appear now and then over time. The OLLA may fail to capture also this variation in an accurate way in analogy with the scenario described above in FIG. 2.